Top Data Analyst Jobs in Bucharest

Develops and maintains forecasting models for clinical site payments, integrating Medidata Payments data and supporting financial reporting. Analyzes plan-versus-actual performance, budget variances, and forecast risks; prepares client-ready reports and reconciliations. Partners with Revenue Recognition, Clinical Operations, Project Analysis, and planning teams to support audits, change orders, study closeouts, compliance, and sponsor reporting requirements.

Analyzes operational data for Client Services, creates and automates management reports, identifies performance issues, and delivers actionable insights and recommendations. The role translates stakeholder needs into analytical requirements, defines data requirements, develops quantitative and qualitative reporting, performs ad hoc analysis using Excel, SQL, Power BI, SAS, Cognos, and Access, and serves as the key data contact for business teams.

Analyze FMCG sales, pricing, promotions, customer, product, margin, market share, and competitor data to support revenue growth management. Develop pricing and price elasticity models, identify commercial opportunities, create visualizations and actionable insights, and translate analytical needs into product requirements, user stories, and business rules. Collaborate with stakeholders, product managers, data engineers, developers, and commercial teams to build scalable digital analytics solutions.

Analyze and improve fraud signals and user segmentation for Puzzleplay’s rewards platform. Investigate suspicious and manually reviewed users, monitor segment effectiveness, identify gaps in detection, and recommend verification tools. Collaborate with product and data teams to turn analysis into operational fraud controls across different markets as fraud patterns evolve.

Owns end-to-end regulatory data analysis and implementation for the Dutch Deposit Guarantee Scheme. Translates DNB and SCV requirements into business rules, mappings, data definitions, controls, and backlog items. Performs multi-source data analysis, lineage and metadata management, data-quality investigations, governance documentation, and remediation coordination. Partners with Product, Data, Technology, Finance, Risk, Compliance, and Regulatory Reporting stakeholders across countries to deliver regulatory milestones and coach colleagues.

Monitor and analyze data activity to identify unauthorized transfers and data leakage incidents. Use DLP metadata to support incident response and forensic investigations, contain incidents, document actions, assess business impact, escalate appropriately, and report to stakeholders. The role also contributes to process improvements, detection-rule tuning, and broader information security initiatives.

Analyzes business requirements, assesses system impacts and feasibility, creates functional and non-functional specifications, supports solution design, development, testing, implementation stabilization, and application acquisition. The role focuses on data management solutions, data warehouses, reporting systems, BI technologies, data integration, and financial services projects while collaborating with business and IT stakeholders.

Analyzes and models data from more than 20 countries to support global KYC services, including transaction monitoring, customer due diligence, and screening. Defines data requirements, quality controls, governance, mappings, and roadmaps while translating business needs into functional solutions. Collaborates with international business and technical stakeholders to improve processes, automate workflows, resolve incidents, and support compliance, anti-money laundering, fraud prevention, and financial crime initiatives.

Analyzes business requirements and their impact on IT systems, translates them into functional and non-functional specifications, supports solution design, development, testing, implementation, and stabilization. Performs feasibility, risk, effort, gap, and functional analysis for data management solutions, including data warehouses and reporting systems. Collaborates with business and IT teams and maintains project documentation.

Own and validate container shipping service data, monitor vessel movements and schedule changes, investigate data-quality issues, query relational databases, support customer data requests, and maintain forecast accuracy. The role requires strong analytical thinking, attention to detail, English fluency, and independent collaboration across time zones. Familiarity with SQL, Power BI, AI tools, and ocean freight operations is beneficial.

Administer and support Planisware PPM systems, ensure data integrity, build automated reports and interactive dashboards (Google Data Studio/SAP Analytics Cloud), develop Excel/Sheets macros, extract/clean project data, and support PMO stakeholders with KPI reporting and documentation.

Coordinates end-to-end data usage requests, helping business teams define needs and validating implementation conditions with legal, compliance, security, and IT stakeholders. Applies data governance standards, monitors KPIs and SLAs, tracks deliverables and budgets, supports reporting, escalates sensitive requests, and improves data usage processes. The role requires strong analytical, communication, project coordination, compliance, and stakeholder management skills, along with fluency in French and English.

Analyzes clinical and operational data to support risk-based quality management and data surveillance. Develops surveillance plans, configures monitoring technologies, evaluates trends and outliers, identifies data quality issues, documents findings, and supports project reviews, meetings, audits, and regulatory inspections. The role requires programming in SAS, R, or SQL, data analysis expertise, familiarity with centralized monitoring and SDTM, and strong communication skills.

Support SEE Growth team by tracking growth KPIs, building and maintaining scalable reports/tools, enabling data access, running ad-hoc analyses, and driving marketing activations from analysis through execution.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Validates, processes, researches, and documents data using queries, sorting, filtering, web research, AI, public sources, and phone outreach. The analyst works with large datasets, identifies defects, verifies data accuracy, and records reproducible issues to support data transformation operations.

Validate migrated and reporting data across source and target systems, with emphasis on SQL-based reconciliation, data quality checks, ETL/ELT validation, discrepancy analysis, and root-cause investigation. Define test scenarios, validate dashboards and KPIs, document defects, and collaborate with Data Engineers and stakeholders. The role also involves testing structured and semi-structured data, profiling datasets, using Python for automation, and supporting modern cloud data-platform delivery.

Early-career Data Analyst responsible for designing and owning core metrics and dashboards, analyzing transaction/customer/credit data to inform credit, fraud, AML, portfolio and growth decisions, building data pipelines and automations with SQL and Python, partnering with cross-functional teams, and owning compliance reporting. Emphasis on turning ambiguous problems into reliable analytical systems and applying GenAI/LLMs for practical automation.

Manage and improve data governance deployment through KPI automation, dashboard development, tool administration, compliance monitoring, requirements analysis, and data catalog adoption. Build QlikSense and Google Looker reporting, automate data collection with AppScript, administer JIRA and Google Sites, support users, and ensure accurate governance metrics. Coordinate tasks and communicate reporting insights to technical and non-technical stakeholders in a multicultural environment.

Analyzes clinical trial scientific and operational data to support risk-based quality management and centralized monitoring. Develops surveillance plans, configures KRIs and statistical analyses, reviews data for trends and outliers, documents findings, escalates quality issues, and collaborates with global project teams. Presents findings in internal and external meetings, supports regulatory inspections, coordinates follow-up actions, and completes central monitoring reports.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.

Act as liaison between business/IT stakeholders and the development squad for IPA SDM and TradeStore. Elicit, analyze and translate business and data requirements into user stories/specifications with acceptance criteria. Define data quality rules, support testing and regression automation, investigate defects, present sprint deliveries, maintain documentation, and drive continuous delivery improvements in an Agile environment.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

Design, build, and maintain Power BI dashboards and Microsoft Fabric data pipelines. Integrate Dynamics 365 data, ensure data quality and governance, deliver executive insights, forecasting, and strategic analysis. Partner with sales, operations, and finance leaders to translate requirements, promote self-service analytics, and document KPIs and reporting logic.

Work with business stakeholders to define and clarify data requirements, create conceptual and logical data models, write specifications for engineers to ingest and structure data into the data lake, design test scenarios and perform functional testing, and maintain metadata (data dictionary). Define data quality, lineage, privacy and security requirements, align with architects on data lake implementation, drive process improvements, and responsibly apply AI tools to streamline tasks.